Meta-analysis of nutritional effects on conjugated linoleic acid (CLA) in milk fat of dairy cows

A meta-analysis was carried out on 41 selected studies to obtain more reliable results about the influence of some nutritional factors on conjugated linoleic acid (CLA) in milk fat. Data were analysed with a linear mixed model, including the study as random variable, that highlighted a significant effect on milk CLA content of fat source and the physical form of the lipid supplement used in the diet. The content of fat in the diet and the forage/concentrate ratio seem do not have significant effects

Studio proteico della parete cellulare di <i>saccharomyces cerevisiae</i> in condizioni di stress

Wine yeasts during alcoholic fermentation and ageing are subjected to several stresses and cell wall is the first compartment involved in the stress response. This PhD thesis deals with the study of the variation in cell wall protein composition in 6 different strains of Saccharomyces cerevisiae (flor/no flor wine strains and laboratory strains). We developed a mass spectrometric method (ESI-Q-TOF) to identify CWPs, unbiased with respect to the covalent linkages to the cell wall carbohydrates. We analysed cell wall protein (CWPs) composition in the studied strains in three different conditions: logarithmic phase and stationary phase in a rich fermenting medium and a flor phase in a minimal medium added with ethanol. In all conditions tested we identified overlapping sets of 20 different proteins. Among them 14 are predicted GPI-modified proteins and 6 are ASL proteins. We choose 5 interesting GPI-proteins and we used qRT-PCR to study related genes in order to identify variation in gene expressions related to different phases

Feminizing adrenocortical carcinoma with distant metastases: can surgery be considered?

Functioning adrenocortical carcinomas are rare diseases with dismal prognosis. A 41-yearold man presenting with gynecomastia had a giant feminizing adrenocortical carcinoma at stage IV. Although surgical resection was controversial, we removed the primary tumor to reduce the mass effects. He lived for 12 months with an acceptable quality of life. Gynecomastia may be the first sign of feminizing adrenal malignancies. Surgery may ameliorate the quality of life in selected patients with metastatic disease

Recenti avanzamenti nella patofisiologia e diagnostica nella malattia di Fabry

Aim Fabry disease (FD) is a rare lysosomal storage disorder caused by deficiency of galactosidaseA that leads to cellular accumulation of glycosphingolipids, causing diffuse vascular damage. Recent scientific reports, including those of our group, led to a better knowledge both of pathophysiology and of biochemical diagnostic tools useful for early diagnosis of FD. We studied possible changes in motor cortex excitability in FD patients, using transcranial magnetic stimulation (TMS). Moreover, we evaluated if urinary glycosaminoglycan excretion could represent a marker for monitoring progressive kidney impairment in FD. Methods We measured the electrical threshold in the motor cortical representation of the right first dorsal interosseous, in 11 FD patients and 11 controls, through TMS protocols. In the biochemical study, quali-quantitative and structural analyses of plasma/urine from 24 FD patients and 43 control subjects were conducted. Results FD patients showed a significant increase of steepness in TMS protocols, which is indicative for an electrophysiological imbalance involving the glutamatergic excitatory circuits. Levels of urine bikunin resulted significantly higher in patients with renal involvement and were higher since early occurrence of renal impairment. Conclusions FD have to be diagnosed in early stage of his course, before occurrence of irreversible structural and vascular damage in many vital organs. New diagnostic tools useful for early diagnosis are needed

Computational models for multilingual negation scope detection

Negation is a common property of languages, in that there are few languages, if any, that lack means to revert the truth-value of a statement. A challenge to cross-lingual studies of negation lies in the fact that languages encode and use it in different ways. Although this variation has been extensively researched in linguistics, little has been done in automated language processing. In particular, we lack computational models of processing negation that can be generalized across language. We even lack knowledge of what the development of such models would require. These models however exist and can be built by means of existing cross-lingual resources, even when annotated data for a language other than English is not available. This thesis shows this in the context of detecting string-level negation scope, i.e. the set of tokens in a sentence whose meaning is affected by a negation marker (e.g. ‘not’). Our contribution has two parts. First, we investigate the scenario where annotated training data is available. We show that Bi-directional Long Short Term Memory (BiLSTM) networks are state-of-the-art models whose features can be generalized across language. We also show that these models suffer from genre effects and that for most of the corpora we have experimented with, high performance is simply an artifact of the annotation styles, where negation scope is often a span of text delimited by punctuation. Second, we investigate the scenario where annotated data is available in only one language, experimenting with model transfer. To test our approach, we first build NEGPAR, a parallel corpus annotated for negation, where pre-existing annotations on English sentences have been edited and extended to Chinese translations. We then show that transferring a model for negation scope detection across languages is possible by means of structured neural models where negation scope is detected on top of a cross-linguistically consistent representation, Universal Dependencies. On the other hand, we found cross-lingual lexical information only to help very little with performance. Finally, error analysis shows that performance is better when a negation marker is in the same dependency substructure as its scope and that some of the phenomena related to negation scope requiring lexical knowledge are still not captured correctly. In the conclusions, we tie up the contributions of this thesis and we point future work towards representing negation scope across languages at the level of logical form as well

Semantic Graph Parsing with Recurrent Neural Network DAG Grammars

Semantic parses are directed acyclic graphs (DAGs), so semantic parsing should be modeled as graph prediction. But predicting graphs presents difficult technical challenges, so it is simpler and more common to predict the linearized graphs found in semantic parsing datasets using well-understood sequence models. The cost of this simplicity is that the predicted strings may not be well-formed graphs. We present recurrent neural network DAG grammars, a graph-aware sequence model that ensures only well-formed graphs while sidestepping many difficulties in graph prediction. We test our model on the Parallel Meaning Bank---a multilingual semantic graphbank. Our approach yields competitive results in English and establishes the first results for German, Italian and Dutch.Comment: 9 pages, to appear in EMNLP201